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Article Update: Find these ETF Signals with my new program
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This is the first in a series of articles which will analyze the strategies contained in Larry Connors’ popular 2009 book Larry Connors’ High Probability ETF Trading which presents 7 strategies for trading highly liquid ETFs. The goal is to determine the statistical significance of the entry points. In other words I want to find out if the entries presented in the book were any better than random over the time period tested.

I will be using EdgeRater to analyze the strategies and this article will present the steps I use along the way so that anyone can follow along and maybe take the analysis further.

3-Day High/Low Method

The first strategy in the book is the 3-Day high/low method. This strategy looks for ETFs that have made lower highs and lower lows for three consecutive days. Combined with a long term moving average to ensure the ETF is generally healthy and a short term average to indicate a pullback the conditions can be written as follows:

  • Today’s close price is above the 200 day SMA
  • Today’s close price is below the 5 day SMA
  • The high price of 2 days ago is below the high price of 3 days ago
  • The low price of 2 days ago is below the low price of 3 days ago
  • The high price of 1 day ago is below the high price of 2 days ago
  • The low price of 1 day ago is below the low price of 2 days ago
  • The high price of today is below the low price of 1 day ago
  • The low price of today is below the low price of 1 day ago

EdgeRater Chart Script

To run the strategy within EdgeRater we need to create a series selector using the above criteria. In this case I will write some Chart Script and assign the final selection to a variable named ‘Event’ – this will allow me to drag and drop the script onto the Series Selector design surface and run script over all of the stocks in the snapshot. The code for the ChartScript is:


Above200:= C > SMA(C,200);
Below5:= C < SMA(C, 5);
HL3:= (Ref(H, 2) < Ref(H, 3)) & (Ref(L, 2) < Ref(L, 3));
HL2:= (Ref(H, 1) < Ref(H, 2)) & (Ref(L, 1) < Ref(L, 2));
HL1:= (H < Ref(H, 1)) & (L < Ref(L, 1));

Event: Above200 & Below5 & HL3 & HL2 & HL1;

EdgeRater symbol list

In his book, Larry claims to have tested his strategies on 20 popular ETFs as follows:

DIA, Diamonds Trust (ETF)
EEM, iShares MSCI Emerging Markets (ETF)
EFA, iShares MSCI EAFE Index (ETF)
EWH, iShares MSCI Hong Kong Index (ETF)
EWJ, iShares MSCI Japan Index (ETF)
EWT, iShares MSCI Taiwan Index (ETF)
EWZ, iShares MSCI Brazil Index (ETF)
FXI, iShares FTSE/Xinhua China 25 Index (ETF)
GLD, SPDR Gold Trust (ETF)
ILF, iShares S&P Latin 40 Index (ETF)
IWM, iShares Russell 2000 Index (ETF)
IYR, iShares Dow Jones U.S. Real Estate (ETF)
QQQQ, PowerShares QQQ Trust (ETF)
SPY, SPDR S&P500 (ETF)
XHB, SPDR S&P Homebuilders (ETF)
XLB, Materials SPDR (ETF)
XLE, Energy Select SPDR (ETF)
XLF, Financial Select SPDR (ETF)
XLI, Industrial SPDR (ETF)
XLV, Health Care Select SPDR (ETF)

To use this list within EdgeRater, create a text file containing the above symbols and names (copy and paste the above to a new text file) and add it to the {EdgeRater}Symbols Lists directory in your documents folder.

EdgeRater data snapshot

Once the list has been created you can easily create a snapshot containing all of the data for those symbols. I built my snapshot using the built-in free Yahoo! data provider. I chose a date range from 1/1/1993 – 12/31/2008.

Running the Analysis

Using the Edge Runner tab within EdgeRater, I selected my freshly created snapshot and checked the box ‘use global exclusion lists’ so that the _INDEX of the snapshot was not included in the results.

Results
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Article Update: Find these ETF Signals with my new program
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It was interesting to see the Event Grid containing events for all of the symbols in the snapshot dating back to 1993. On my laptop running Windows 7 this result was generated in 1/10th of a second – not bad for a sub $700 dollar laptop, and excellent for allowing me to experiment with different parameters.

Here’s a screen shot of part of the event grid where you can see the symbols that EdgeRater has selected. I chose to capture a screen shot of the 07/18/2007 column because that is the date that Larry uses for the EEM example ‘event’ in his book:

Event grid after the 3-day high/low selector has run

Event grid after the 3-day high/low selector has run

Shameless plug…

I find this grid extremely helpful because not only does it show me the stocks that met the criteria today, but it also shows the stocks that met the criteria for every historical day in the analysis period. In other scanning applications that pick out stocks that met criteria for today only, I’m often left wondering what is going to happen to those stocks and trying to remember to come back to my computer in a few days to find out. EdgeRater shows me all the results for all previous days in the grid and I can just double click on any of those items to see a stock chart with the event highlighted so that I can see what happened next.

Statistics
Using the Results tab I took a look at the statistics of the selections and found out what the average gain was after ‘N’ bars of the event occurring. Here’s a screen shot showing the statistics of gain/loss 4 days after the event:

3-Day High/Low gain loss frequency

3-Day High/Low gain loss frequency

The mean value was +.5474% with a standard deviation of 2.8719

Baseline

The gain/loss frequency chart looks really interesting, showing an average of .5474% gain in 4 days. However, that gain might have been due to the general market behavior and nothing to do with the chosen entry points and so I ran a baseline scan which shows the average of all stocks, not just the ones that met the criteria. Here’s the result of the baseline scan:

Gain Loss Frequency - Baseline

The mean value was +.0944% with a standard deviation of 3.4776, so the baseline scan does have a positive expectation when holding for 4 days which indicates that the market as a whole was gaining during the analysis period, but that gain is far lower than the gain when taking the 3-day high/low entry.

Summary

The first strategy in Larry Connors’ ‘High Probability ETF Trading book’ – the 3-Day High/Low Method looks like it produces entries with a positive edge compared to a baseline entry point. This is the first test that I would run on any proposed strategy and in this case it warrants further investigation. EdgeRater is a great tool for designing and exploring many different strategies and I would encourage the reader to view the other reports that are available in the application such as the simulated trade reports including the daily equity chart.

I am now interested in running an analysis of the short entry method for the same time period – if that also has positive expectation I may well be running these on a nightly basis to find trade candidates for my trading account.

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Chris White
CEO, EdgeRater LLC